Brieflow: An Integrated Computational Pipeline for High-Throughput Analysis of Optical Pooled Screening Data

Area of Science:

• Functional genomics
• Cellular morphology
• High-content screening

Background:

• Optical pooled screening (OPS) enables large-scale linking of genetic perturbations to cellular phenotypes.
• Challenges in OPS data analysis include massive datasets and complex integration requirements.
• Standardized frameworks for OPS data analysis are lacking.

Purpose of the Study:

• To present Brieflow, a computational pipeline for end-to-end analysis of fixed-cell optical pooled screening data.
• To demonstrate Brieflow's capability in processing large-scale OPS datasets.
• To improve the discovery of biological insights from high-content phenotypic screening.

Main Methods:

• Developed Brieflow, an open-source computational pipeline.
• Applied Brieflow to reanalyze a CRISPR-Cas9 screen of 5,072 genes.
• Processed over 70 million cells with multiple phenotypic markers.

Main Results:

• Identified novel functional gene relationships missed in the original study.
• Uncovered biological insights in mitochondrial function, mRNA processing, vesicular trafficking, and MYC transcriptional control.
• Demonstrated Brieflow's ability to handle massive datasets and multi-modal data integration.

Conclusions:

• Brieflow provides a modular and reproducible framework for OPS data analysis.
• The pipeline enhances computational performance and facilitates biological discovery.
• Brieflow supports the integration of novel analytical components for advanced phenotypic screening.